48 citations · 77 across the 16 of their papers we have counts for
6 papers · 1 filter
SLOSH: Set LOcality Sensitive Hashing via Sliced-Wasserstein Embeddings
Yuzhe Lu, Xinran Liu, Andrea Soltoggio +1
Learning from set-structured data is an essential problem with many applications in machine learning and computer vision. This paper focuses on non-parametric and data-independent…
Circle Representation for Medical Object Detection
Ethan H. Nguyen, Haichun Yang, Ruining Deng +7
Box representation has been extensively used for object detection in computer vision. Such representation is efficacious but not necessarily optimized for biomedical objects (e.g.,…
Compressive Neural Representations of Volumetric Scalar Fields
Yuzhe Lu, Kairong Jiang, Joshua A. Levine +1
We present an approach for compressing volumetric scalar fields using implicit neural representations. Our approach represents a scalar field as a learned function, wherein a neura…
SimTriplet: Simple Triplet Representation Learning with a Single GPU
Quan Liu, Peter C. Louis, Yuzhe Lu +9
Contrastive learning is a key technique of modern self-supervised learning. The broader accessibility of earlier approaches is hindered by the need of heavy computational resources…
Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis
Yuzhe Lu, Aadarsh Jha, Yuankai Huo
Annotated medical images are typically rarer than labeled natural images since they are limited by domain knowledge and privacy constraints. Recent advances in transfer and contras…
Improve Global Glomerulosclerosis Classification with Imbalanced Data using CircleMix Augmentation
Yuzhe Lu, Haichun Yang, Zheyu Zhu +3
The classification of glomerular lesions is a routine and essential task in renal pathology. Recently, machine learning approaches, especially deep learning algorithms, have been u…